Zobrazeno 1 - 10
of 184
pro vyhledávání: '"Krzysztof J. Cios"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 5, Iss 3, Pp 1010-1022 (2023)
The use of back propagation through the time learning rule enabled the supervised training of deep spiking neural networks to process temporal neuromorphic data. However, their performance is still below non-spiking neural networks. Previous work poi
Externí odkaz:
https://doaj.org/article/0f2d9017289f4dd9bf2f38bb716ad01d
Publikováno v:
Frontiers in Computational Neuroscience, Vol 15 (2021)
In this paper we present a Competitive Rate-Based Algorithm (CRBA) that approximates operation of a Competitive Spiking Neural Network (CSNN). CRBA is based on modeling of the competition between neurons during a sample presentation, which can be red
Externí odkaz:
https://doaj.org/article/98b6d52497b54748b4bbcaa2391fc6d5
Publikováno v:
Journal of Systemics, Cybernetics and Informatics, Vol 4, Iss 6, Pp 41-46 (2006)
This article describes the design of an interactive learning environment to increase student achievement in middle schools by addressing students' preconceptions, and promoting purposeful social collaboration, distributed cognition, and contextual le
Externí odkaz:
https://doaj.org/article/30c2de528dca4bfd9b6ec6f30c0b6003
Publikováno v:
Electronics; Volume 11; Issue 23; Pages: 3909
Deep convolutional neural networks are often used for image verification but require large amounts of labeled training data, which are not always available. To address this problem, an unsupervised deep learning face verification system, called UFace
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46377eefab81e095cf397b95b323fb9a
Publikováno v:
2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98e2a4e269a3ffb189a6d64df446c7b7
https://doi.org/10.1109/icecs202256217.2022.9970967
https://doi.org/10.1109/icecs202256217.2022.9970967
Autor:
Enoch Solomon, Krzysztof J. Cios
Publikováno v:
Electronics; Volume 12; Issue 10; Pages: 2199
Face recognition technology has been widely used due to the convenience it provides. However, face recognition is vulnerable to spoofing attacks which limits its usage in sensitive application areas. This work introduces a novel face anti-spoofing sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba8ba4a5cd0d98cd5b1acca4d8276757
https://doi.org/10.3390/electronics12102199
https://doi.org/10.3390/electronics12102199
Publikováno v:
Information Fusion. 50:168-180
In recent years, the multi-label classification task has gained the attention of the scientific community given its ability to solve problems where each of the instances of the dataset may be associated with several class labels at the same time inst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f729ec860ae7c7d59485bfe89567ac8
https://doi.org/10.1016/j.inffus.2018.11.013
https://doi.org/10.1016/j.inffus.2018.11.013
Publikováno v:
Frontiers in Computational Neuroscience
Frontiers in Computational Neuroscience, Vol 15 (2021)
Frontiers in Computational Neuroscience, Vol 15 (2021)
In this paper we present a Competitive Rate-Based Algorithm (CRBA) that approximates operation of a Competitive Spiking Neural Network (CSNN). CRBA is based on modeling of the competition between neurons during a sample presentation, which can be red
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a58d1e14a4a6fe12e740f5e4e3d1ca05
Publikováno v:
CEC
Multi-label classification paradigm has had a growing interest because of the emergence of a large number of classification problems where each of the instances of the data can be associated with several output labels simultaneously. Several ensemble
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fcef847898fdfb14fe6817db8432a0f8
https://doi.org/10.1109/cec48606.2020.9185661
https://doi.org/10.1109/cec48606.2020.9185661
Publikováno v:
Information Processing and Management of Uncertainty in Knowledge-Based Systems ISBN: 9783030501525
IPMU (3)
IPMU (3)
Recent work on spiking neural networks showed good progress towards unsupervised feature learning. In particular, networks called Competitive Spiking Neural Networks (CSNN) achieve reasonable accuracy in classification tasks. However, two major disad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc535e20177953d18a68207f7797a569
https://doi.org/10.1007/978-3-030-50153-2_57
https://doi.org/10.1007/978-3-030-50153-2_57
